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Journal of Bioinformatics and Computational Biology

Mohammad Mohebbi, Liang Ding, Russell L Malmberg, Cory Momany, Khaled Rasheed, Liming Cai
miRNAs are involved in many critical cellular activities through binding to their mRNA targets, e.g. in cell proliferation, differentiation, death, growth control, and developmental timing. Accurate prediction of miRNA targets can assist efficient experimental investigations on the functional roles of miRNAs. Their prediction, however, remains a challengeable task due to the lack of experimental data about the tertiary structure of miRNA-target binding duplexes. In particular, correlations of nucleotides in the binding duplexes may not be limited to the canonical Watson Crick base pairs (BPs) as they have been perceived; methods based on secondary structure prediction (typically minimum free energy (MFE)) have only had mix success...
May 7, 2018: Journal of Bioinformatics and Computational Biology
Indrani Ray, Abhijit Dasgupta, Rajat K De
The incidence and prevalence of nonalcoholic fatty liver disease (NAFLD) have been increasing to epidemic proportions around the world. NAFLD, a chronic liver disease that affects the nondrinkers, is mainly associated with steatohepatitis and cirrhosis. The progression of NAFLD associated with obesity increases the risk of liver cancer, a disease with poor outcomes and limited therapeutic options. In order to investigate the underlying cellular dynamics leading to NAFLD progression towards cancer on the onset of obesity, we have integrated human hepatocyte pathway with hypoxia-inducible factor1-[Formula: see text] (HIF1-[Formula: see text]) signaling pathway using state space model based on classical control theory...
April 26, 2018: Journal of Bioinformatics and Computational Biology
Jiyun Choi, Kipoong Kim, Hokeun Sun
In genetic association studies, regularization methods are often used due to their computational efficiency for analysis of high-dimensional genomic data. DNA methylation data generated from Infinium HumanMethylation450 BeadChip Kit have a group structure where an individual gene consists of multiple Cytosine-phosphate-Guanine (CpG) sites. Consequently, group-based regularization can precisely detect outcome-related CpG sites. Representative examples are sparse group lasso (SGL) and network-based regularization...
April 26, 2018: Journal of Bioinformatics and Computational Biology
Bangli Lu, Chen Li, Qingfeng Chen, Jiangning Song
Protein-protein binding interaction is the most prevalent biological activity that mediates a great variety of biological processes. The increasing availability of experimental data of protein-protein interaction allows a systematic construction of protein-protein interaction networks, significantly contributing to a better understanding of protein functions and their roles in cellular pathways and human diseases. Compared to well-established classification for protein-protein interactions (PPIs), limited work has been conducted for estimating protein-protein binding free energy, which can provide informative real-value regression models for characterizing the protein-protein binding affinity...
April 26, 2018: Journal of Bioinformatics and Computational Biology
Amr Alhossary, Yaw Awuni, Chee Keong Kwoh, Yuguang Mu
Dengue fever is a febrile illness caused by Dengue Virus, which belongs to the Flaviviridae family. Among its proteome, the nonstructural protein 5 (NS5) is the biggest and most conserved. It has a primer-independent RNA-dependent RNA polymerase (RdRp) domain at its C-Terminus. Zou et al. studied the biological relevance of the two conserved cavities (named A and B) within the NS5 proteins of dengue virus (DENV) and West Nile Virus (WNV) using mutagenesis and revertant analysis and found four mutations located at cavity B having effects on viral replication...
June 2018: Journal of Bioinformatics and Computational Biology
Naoki Arai, Shunsuke Yoshikawa, Nobuaki Yasuo, Ryunosuke Yoshino, Masakazu Sekijima
During drug discovery, drug candidates are narrowed down over several steps to develop pharmaceutical products. The theoretical chemical space in such steps is estimated to be [Formula: see text]. To cover that space, extensive virtual compound libraries have been developed; however, the compilation of extensive libraries comes at large computational cost. Thus, to reduce the computational cost, researchers have constructed custom-made virtual compound libraries that focus on target diseases. In this study, we develop a system that generates virtual compound libraries from input compounds...
June 2018: Journal of Bioinformatics and Computational Biology
Lee Sael
No abstract text is available yet for this article.
June 2018: Journal of Bioinformatics and Computational Biology
Amir Zeb, Chanin Park, Minky Son, Shailima Rampogu, Syed Ibrar Alam, Seok Ju Park, Keun Woo Lee
Proteins deacetylation by Histone deacetylase 6 (HDAC6) has been shown in various human chronic diseases like neurodegenerative diseases and cancer, and hence is an important therapeutic target. Since, the existing inhibitors have hydroxamate group, and are not HDAC6-selective, therefore, this study has designed to investigate non-hydroxamate HDAC6 inhibitors. Ligand-based pharmacophore was generated from 26 training set compounds of HDAC6 inhibitors. The statistical parameters of pharmacophore (Hypo1) included lowest total cost of 115...
June 2018: Journal of Bioinformatics and Computational Biology
Turki Turki, Zhi Wei, Jason T L Wang
Transfer learning (TL) algorithms aim to improve the prediction performance in a target task (e.g. the prediction of cisplatin sensitivity in triple-negative breast cancer patients) via transferring knowledge from auxiliary data of a related task (e.g. the prediction of docetaxel sensitivity in breast cancer patients), where the distribution and even the feature space of the data pertaining to the tasks can be different. In real-world applications, we sometimes have a limited training set in a target task while we have auxiliary data from a related task...
June 2018: Journal of Bioinformatics and Computational Biology
Maria Satti, Yasuhiro Tanizawa, Akihito Endo, Masanori Arita
The commensal genus Bifidobacterium has probiotic properties. We prepared a public library of the gene functions of the genus Bifidobacterium for its online annotation. Orthologous gene cluster analysis showed that the pan genomes of Bifidobacterium and Lactobacillus exhibit striking similarities when mapped to the Clusters of Orthologous Group (COG) database of proteins. When the core genes in each genus were selected based on our statistical definition of "core genome", core genes were present in at least 92% of 52 Bifidobacterium and in 97% of 178 Lactobacillus genomes...
June 2018: Journal of Bioinformatics and Computational Biology
Mikhail Gelfand
No abstract text is available yet for this article.
April 2018: Journal of Bioinformatics and Computational Biology
Evgeny E Akkuratov, Mikhail S Gelfand, Ekaterina E Khrameeva
Sequencing of complete nuclear genomes of Neanderthal and Denisovan stimulated studies about their relationship with modern humans demonstrating, in particular, that DNA alleles from both Neanderthal and Denisovan genomes are present in genomes of modern humans. The Papuan genome is a unique object because it contains both Neanderthal and Denisovan alleles. Here, we have shown that the Papuan genomes contain different gene functional groups inherited from each of the ancient people. The Papuan genomes demonstrate a relative prevalence of Neanderthal alleles in genes responsible for the regulation of transcription and neurogenesis...
April 2018: Journal of Bioinformatics and Computational Biology
Oxana A Volkova, Yury V Kondrakhin, Timur A Kashapov, Ruslan N Sharipov
RNA plays an important role in the intracellular cell life and in the organism in general. Besides the well-established protein coding RNAs (messenger RNAs, mRNAs), long non-coding RNAs (lncRNAs) have gained the attention of recent researchers. Although lncRNAs have been classified as non-coding, some authors reported the presence of corresponding sequences in ribosome profiling data (Ribo-seq). Ribo-seq technology is a powerful experimental tool utilized to characterize RNA translation in cell with focus on initiation (harringtonine, lactimidomycin) and elongation (cycloheximide)...
April 2018: Journal of Bioinformatics and Computational Biology
Óscar Álvarez, Juan Luis Fernández-Martínez, Celia Fernández-Brillet, Ana Cernea, Zulima Fernández-Muñiz, Andrzej Kloczkowski
We discuss applicability of principal component analysis (PCA) for protein tertiary structure prediction from amino acid sequence. The algorithm presented in this paper belongs to the category of protein refinement models and involves establishing a low-dimensional space where the sampling (and optimization) is carried out via particle swarm optimizer (PSO). The reduced space is found via PCA performed for a set of low-energy protein models previously found using different optimization techniques. A high frequency term is added into this expansion by projecting the best decoy into the PCA basis set and calculating the residual model...
April 2018: Journal of Bioinformatics and Computational Biology
Myungjin Moon, Kenta Nakai
Currently, cancer biomarker discovery is one of the important research topics worldwide. In particular, detecting significant genes related to cancer is an important task for early diagnosis and treatment of cancer. Conventional studies mostly focus on genes that are differentially expressed in different states of cancer; however, noise in gene expression datasets and insufficient information in limited datasets impede precise analysis of novel candidate biomarkers. In this study, we propose an integrative analysis of gene expression and DNA methylation using normalization and unsupervised feature extractions to identify candidate biomarkers of cancer using renal cell carcinoma RNA-seq datasets...
April 2018: Journal of Bioinformatics and Computational Biology
Hossam M Ashtawy, Nihar R Mahapatra
Predicting the native poses of ligands correctly is one of the most important steps towards successful structure-based drug design. Binding affinities (BAs) estimated by traditional scoring functions (SFs) are typically used to score and rank-order poses to select the most promising conformation. This BA-based approach is widely applied and some success has been reported, but it is inconsistent and still far from perfect. The main reason for this is that SFs are trained on experimental BA values of only native poses found in co-crystallized structures of protein-ligand complexes (PLCs)...
April 2018: Journal of Bioinformatics and Computational Biology
Ekaterina Myasnikova, Alexander Spirov
Commonly among the model parameters characterizing complex biological systems are those that do not significantly influence the quality of the fit to experimental data, so-called "sloppy" parameters. The sloppiness can be mathematically expressed through saturating response functions (Hill's, sigmoid) thereby embodying biological mechanisms responsible for the system robustness to external perturbations. However, if a sloppy model is used for the prediction of the system behavior at the altered input (e...
April 2018: Journal of Bioinformatics and Computational Biology
Alexander M Andrianov, Ivan A Kashyn, Alexander V Tuzikov
An integrated computational approach to in silico drug design was used to identify novel HIV-1 fusion inhibitor scaffolds mimicking broadly neutralizing antibody (bNab) 10E8 targeting the membrane proximal external region (MPER) of the HIV-1 gp41 protein. This computer-based approach included (i) generation of pharmacophore models representing 3D-arrangements of chemical functionalities that make bNAb 10E8 active towards the gp41 MPER segment, (ii) shape and pharmacophore-based identification of the 10E8-mimetic candidates by a web-oriented virtual screening platform pepMMsMIMIC, (iii) high-throughput docking of the identified compounds with the gp41 MPER peptide, and (iv) molecular dynamics simulations of the docked structures followed by binding free energy calculations...
April 2018: Journal of Bioinformatics and Computational Biology
Dmitry Suplatov, Yana Sharapova, Daria Timonina, Kirill Kopylov, Vytas Švedas
The visualCMAT web-server was designed to assist experimental research in the fields of protein/enzyme biochemistry, protein engineering, and drug discovery by providing an intuitive and easy-to-use interface to the analysis of correlated mutations/co-evolving residues. Sequence and structural information describing homologous proteins are used to predict correlated substitutions by the Mutual information-based CMAT approach, classify them into spatially close co-evolving pairs, which either form a direct physical contact or interact with the same ligand (e...
April 2018: Journal of Bioinformatics and Computational Biology
Ekaterina N Grafskaia, Nadezhda F Polina, Vladislav V Babenko, Daria D Kharlampieva, Pavel A Bobrovsky, Valentin A Manuvera, Tatyana E Farafonova, Nikolay A Anikanov, Vassili N Lazarev
As essential conservative component of the innate immune systems of living organisms, antimicrobial peptides (AMPs) could complement pharmaceuticals that increasingly fail to combat various pathogens exhibiting increased resistance to microbial antibiotics. Among the properties of AMPs that suggest their potential as therapeutic agents, diverse peptides in the venoms of various predators demonstrate antimicrobial activity and kill a wide range of microorganisms. To identify potent AMPs, the study reported here involved a transcriptomic profiling of the tentacle secretion of the sea anemone Cnidopus japonicus...
April 2018: Journal of Bioinformatics and Computational Biology
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